Presently, aircraft such as helicopters undergo evaluation with respect to fatigue damage in a very conservative manner based on calculations which rely on assumptions of worst case aircraft usage because of a lack of detailed logging of maneuvers flown. Aircraft components are accordingly often replaced at unnecessarily frequent intervals based on estimations derived from such conservative assumptions.
In connection with rotor craft, a variable state data estimating system has already been disclosed in U.S. Pat. No. 5,751,609 in connection with the calculation of airspeed, involving use of a programmed neural network. The use of a neural network involving pattern recognition has been disclosed in U.S. Pat. No. 5,180,911 to Grossman et al., in regard to value measurement of a variable state parameter such as structural strain. However such prior art analytical or neural network systems are not applied to accurate recognition and identification of aircraft flight regimes, so as to provide a reliable basis for evaluating flight usage of aircraft components, as an important object of the present invention.